Under the background of urbanization and the rapid development of urban rail transit (URT), serious attention has been focused on URT network reliability in recent years. In this work, in order to measure network reliability, three indicators are constructed based on passengers' tolerable travel paths, passenger travel efficiency and passenger travel realization on a URT network. The passenger tolerability coefficient, which is the ratio of passengers' tolerable travel time to the shortest possible travel time, is proposed and added to the indicators. It reflects passengers' behavior with respect to choice of travel paths. The ratio of affected passenger volume (RAPV) is proposed to identify important stations. Finally, the connectivity reliability of Wuhan's subway network is analyzed by simulating attacks on stations. The results show that the degree centrality, betweenness centrality and RAPV indicators of stations can effectively identify the important stations that have a significant impact on the connectivity reliability of the network. In particular, the RAPV indicator effectively identifies stations that have the greatest influence on passenger travel realization. The connectivity reliability of Wuhan's subway network is sensitive to passenger tolerability coefficient, and reliability is greater during non-peak hours than during peak hours. In addition, the stations that are important to the connectivity reliability of the Wuhan subway have two features, i.e., they are located at the center of the city, and they are important for connecting subgraphs of the network.
An urban rail transit (URT) system is an important component of an urban infrastructure system; however, it is vulnerable to disturbances, such as natural disasters and terrorist attacks. Constructing a highly resilient URT network has practical significance for enhancing its capability to respond to disturbances. In this paper, models are developed to optimize a URT network’s structure with regard to resilience and to enhance the resilience of a disrupted URT network. A bi-level programming model that aims to maximize a URT network’s global accessibility and global efficiency is formulated to optimize the structure of the network. A novel repair strategy, called the simulation repair strategy, is proposed to enhance the resilience of a disrupted URT network by optimizing the repair sequence of failed stations. The models are utilized to enhance the resilience of the Chengdu subway network. The result indicates that the bi-level programming model guides the construction of new links to optimize the structure of the Chengdu subway network. Deliberate attacks are more harmful to the Chengdu subway network than random attacks. The network’s operators need to pay attention to the operations of critical stations (e.g., Chunxi Road station and Tianfu Square station) to prevent disturbances from exerting considerable negative effects on the network’s normal operations. The simulation repair strategy exhibits higher repair efficiency than the conventional repair strategy, and it effectively enhances the resilience of the disrupted Chengdu subway network.
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